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An automated image analysis framework for segmentation and division plane detection of single live Staphylococcus aureus cells which can operate at millisecond sampling time scales using bespoke Slimfield microscopy

Abstract:
Staphylococcus aureus is an important pathogen, giving rise to antimicrobial resistance in cell strains such as Methicillin Resistant S. aureus (MRSA). Here we report an image analysis framework for automated detection and image segmentation of cells in S. aureus cell clusters, and explicit identification of their cell division planes.Weuse a new combination of several existing analytical tools of image analysis to detect cellular and subcellular morphological features relevant to cell division from millisecond time scale sampled images of live pathogens at a detection precision of single molecules.Wedemonstrate this approach using a fluorescent reporter GFP fused to the protein EzrA that localises to a mid-cell plane during division and is involved in regulation of cell size and division. This image analysis framework presents a valuable platform from which to study candidate new antimicrobials which target the cell division machinery, but may also have more general application in detecting morphologically complex structures of fluorescently labelled proteins present in clusters of other types of cells.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1088/1478-3975/13/5/055002

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Condensed Matter Physics
Role:
Author
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Role:
Author
ORCID:
0000-0002-1715-1249


Publisher:
Institute of Physics
Journal:
Physical Biology More from this journal
Volume:
13
Issue:
5
Pages:
055002
Publication date:
2016-10-17
Acceptance date:
2016-09-07
DOI:
EISSN:
1478-3975
ISSN:
1478-3967


Keywords:
Pubs id:
pubs:821226
UUID:
uuid:c962e580-e0d3-4729-b52a-254f1409a41b
Local pid:
pubs:821226
Source identifiers:
821226
Deposit date:
2018-04-11

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